基于單變量降維模型和坐標旋轉的可靠度混合分析方法
[Abstract]:The classical first-order reliability method has the applicability problem to the problem of implicit function and strongly nonlinear function, although the quadratic reliability method can deal with the problem of strong nonlinear function to some extent. However, the theoretical basis and calculation process are quite complex, which is not conducive to practical. In order to overcome the above problems, it is an effective way to combine the process of determining the checking point with the method of response surface. For this reason, this paper first introduces a universal first-order reliability method, in which the Nataf transformation of correlated non-normal random variables is considered, and the unilateral difference method is introduced to solve the problem of implicit function finding partial derivative. According to the gradient value, the coordinate rotation vector is introduced, and the univariate function reduced dimension approximate model is introduced to the rotated function. Thirdly, the function value, gradient value and additional point function value of the checking point are combined. Determine the quadratic polynomial approximation of each component function, and obtain the approximate global function. Then, the importance sampling method is used to calculate the failure probability of the approximate functional function. The accuracy and efficiency of the method are verified by numerical examples and engineering examples respectively. The results show that the proposed method has the characteristics of high accuracy and high efficiency, and it is widely applicable to both explicit and implicit function functions.
【作者單位】: 重慶大學山地城鎮(zhèn)建設與新技術教育部重點實驗室;重慶大學土木工程學院;美國加州大學歐文分校;
【基金】:國家自然科學基金(51678092,51478064,50908243)
【分類號】:TB114.3
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